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<table width="100%" summary="page for Mammals"><tr><td>Mammals</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Garland(1983) Data on Running Speed of Mammals</h2>

<h3>Description</h3>

<p>Observations on the maximal running speed of mammal species
and their body mass.
</p>


<h3>Usage</h3>

<pre>data(Mammals)</pre>


<h3>Format</h3>

<p>A data frame with 107 observations on the following 4 variables.
</p>

<dl>
<dt>weight</dt><dd><p>Body mass in Kg for &quot;typical adult sizes&quot;</p>
</dd>
<dt>speed</dt><dd><p>Maximal running speed (fastest sprint velocity on record)</p>
</dd>
<dt>hoppers</dt><dd><p>logical variable indicating animals that ambulate
by hopping, e.g. kangaroos</p>
</dd>
<dt>specials</dt><dd><p>logical variable indicating special animals with
&quot;lifestyles in which speed does not figure as an important
factor&quot;:  Hippopotamus, raccoon (Procyon), badger (Meles),
coati (Nasua), skunk (Mephitis), man (Homo), porcupine
(Erithizon), oppossum (didelphis), and sloth (Bradypus)
</p>
</dd>
</dl>



<h3>Details</h3>

<p>Used by Chappell (1989) and Koenker, Ng and Portnoy (1994) to
illustrate the fitting of piecewise linear curves.
</p>


<h3>Source</h3>

<p>Garland, T. (1983) The relation between maximal running speed and body 
mass in terrestrial mammals, <em>J. Zoology</em>, 199, 1557-1570.
</p>


<h3>References</h3>

<p>Koenker, R., P. Ng and S. Portnoy, (1994)  Quantile Smoothing Splines&rdquo; 
<em>Biometrika</em>, 81, 673-680.
</p>
<p>Chappell, R. (1989) Fitting Bent Lines to Data, with Applications ot
Allometry,  <em>J. Theo. Biology</em>, 138, 235-256.
</p>


<h3>See Also</h3>

<p><code>rqss</code></p>


<h3>Examples</h3>

<pre>
data(Mammals)
attach(Mammals)
x &lt;- log(weight)
y &lt;- log(speed)
plot(x,y, xlab="Weight in log(Kg)", ylab="Speed in log(Km/hour)",type="n")
points(x[hoppers],y[hoppers],pch = "h", col="red")
points(x[specials],y[specials],pch = "s", col="blue")
others &lt;- (!hoppers &amp; !specials)
points(x[others],y[others], col="black",cex = .75)
fit &lt;- rqss(y ~ qss(x, lambda = 1),tau = .9)
plot(fit)
</pre>


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